Time Series Forecasting
Transformers
Safetensors
t5
text2text-generation
TSFM
Finance
Financial Forecasting
FinText
text-generation-inference
Instructions to use FinText/Chronos_Small_2020_US with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FinText/Chronos_Small_2020_US with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("FinText/Chronos_Small_2020_US") model = AutoModelForSeq2SeqLM.from_pretrained("FinText/Chronos_Small_2020_US") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fff1191ef5883c30749535bd54201b902b54a86acf262f7d107cd1c1c98f4acc
- Size of remote file:
- 185 MB
- SHA256:
- 89f1e59c3b6af98b6194b2658d189f71cf39934ba957b197e73de0222419339c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.